Lai
Senior · Staff · Principal Machine Learning Engineer
New York
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hirly's read of this role
- Role family
- Data & ML
- Seniority
- Lead / management
- Country
- US
- Work mode
- On-site / unstated
- First seen by hirly
- 1 Sept 2026
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the posting
Senior / Staff / Principal Machine Learning Engineer
Location: Onsite New York (5 days onsite AND hybrid options)
We have multiple startups interested in talent. Here is a generic summary. Instead of a perfect job description, we present talented individuals to companies and allow them to share how that talent fits in the organization.
Key Responsibilities:
- Model Development:
- Designing and implementing ML algorithms and models, including deep learning models.
- Data Handling:
- Preprocessing, analyzing, and preparing large datasets for model training and evaluation.
- System Integration:
- Collaborating with software engineers to integrate ML models into production systems.
- Performance Optimization:
- Continuously improving and optimizing ML models for accuracy, efficiency, and scalability.
- Monitoring and Maintenance:
- Monitoring model performance in production, troubleshooting issues, and ensuring model reliability.
- Staying Updated:
- Keeping abreast of the latest advancements in ML, AI, and related technologies.
- Collaboration:
- Working with data scientists, software engineers, and other stakeholders to deliver effective ML solutions.
Essential Skills:
Programming Languages: Strong proficiency in Python, R, or other relevant languages.
ML Frameworks: Experience with frameworks like TensorFlow, PyTorch, or scikit-learn.
Data Science Fundamentals: Solid understanding of statistical analysis, data modeling, and machine learning algorithms.
Problem-Solving: Excellent analytical and problem-solving skills to address complex challenges.
Communication: Effective communication skills to convey technical information to both technical and non-technical audiences.
Collaboration: Ability to work effectively in a team environment.
Education and Experience:
A bachelor's or master's degree in computer science, engineering, mathematics, statistics, or a related field is typically required.
Several years of experience in machine learning, data science, or software development is often preferred.
Compensation: Market range and can include equity – details can be provided after the specific client is determined.
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